[1]} proposed an efficient method for sampling from diffusion probabilistic models by a dynamic programming algorithm that finds the optimal discrete time schedules. [2]} introduces the Iterative Latent Variable Refinement (ILVR) method for guiding the generative process in DDPM. Moreover, [3]} systematically investigates fast sampling methods for diffusion denoising models. [4]} propose bilateral denoising diffusion models (BDDM), which take significantly fewer steps to generate high-quality samples.
